Conventional approaches to the assessment of human health effects of exposure to contaminant mixtures from hazardous waste sites often fail to provide useful results due to: (1) limitation of studies to a single chemical compound; (2) limitations on the identification of the exposed population; and (3) the use of health effect endpoints that either involve long latency periods, or are so infrequent that statistical power is extremely low. This project addresses some of these problems by developing a health surveillance model to study in endpoint detectable contemporaneously with exposure. The hypotheses tested by this study are that improved definition of populations exposed to hazardous chemical waste mixtures can be achieved by the use of (1) reproductive outcome as a epidemiological surveillance tool; (2) geographic information system technology for spatial data analysis; and (3) biochemical parameters measured in common invertebrates as indices of exposure. The sources of data for this study are from Remedial Investigation/Feasibility Studies and vital statistic records for listed Superfund sites. The population at risk will be identified with the aid of spatial statistics and cartographic modeling using geographic information system (GIS) technology. The model will also be used to evaluate environmental biological monitoring of terrestrial and aquatic contamination as an endpoint for identifying potentially exposed populations. Reproductive outcomes (birth weight, gestational age and fertility) as surveillance variables could be useful for all hazardous waste sites because this data will be available in any state. The identification of high risk populations will allow more detailed analytical studies in populations with potential effects to be conducted in a more time and cost efficient manner. Biochemical endpoints sensitive to toxic chemical exposure (including cytochrome P450 and metal- binding protein induction) will be determined in common invertebrates to provide an assessment of the extent of dispersion of contaminants from a hazardous waste site. This will help define the geographic boundaries of exposure via actual pathways. GIS analysis will provide a method for integrating the large data base generated by this study as well as that obtained from existing contaminant monitoring approaches and will allow analysis of spatial relationships between chemical concentration data and biological endpoints. These approaches will be well suited to the assessment of exposures to complex mixtures of contaminants.